Hierarchical Clustering Analysis of Biopharmaceuticals Crop Production Across Indonesian Provinces - Mayang Anglingsari Putri; Ismail Hasvi; Deby Ananda Difah; Miratul Alifah; Fifin Ayu Mufarroha; Irawati Nurmalasari; Irpan Kusyadi (Institut Teknologi, Sains, dan Kesehatan RS.DR. Soepraoen Kesdam V/BRW, 2026)
This study analyzes biopharmaceuticals (medicinal crop) production across Indonesian provinces using 2023 data from eight major commodities: ginger, galangal, kencur, turmeric, lempuyang, temulawak, temu ireng, and keji beling. Data from 38 provinces were normalized and analyzed using agglomerative hierarchical clustering with Ward’s linkage and Euclidean distance. The results identify three distinct clusters representing high, medium, and low production levels, with Java provinces dominating the high-production cluster, while provinces outside Java fall into moderate and low clusters. These findings highlight regional disparities and potential specialization in biopharmaceuticals cultivation. This study contributes a comprehensive national-scale multivariate clustering framework for medicinal crop production and demonstrates the applicability of hierarchical clustering for spatial agricultural analysis. The findings provide practical implications for policymakers in designing targeted agricultural development strategies, regional specialization planning, and supply chain optimization in Indonesia’s biopharmaceuticals sector.